Quantifying the contribution of environmental variables to cyclists’ exposure to PM2.5 using machine learning techniques-Reference-Cited by-同舟云学术

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Quantifying the contribution of environmental variables to cyclists’ exposure to PM2.5 using machine learning techniques

Published:2024-01 Issue:2 Volume:10 Page:e24724
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Rodríguez Núñez Martín,Tavera Busso Iván,Carreras Hebe Alejandra^ORCID

Funder

Agencia Nacional De Promoción Científica Y Tecnológica

Universidad Nacional de Cordoba

Agencia Nacional de Promoción Científica y Tecnológica

Universidad de Córdoba

Publisher

Elsevier BV

Reference84 articles.

1. Cyclists' exposure to air pollution: in situ evaluation with a cargo bike platform;Carreras;Environ. Monit. Assess.,2020

2. Cycling as a smart and green mode of transport in small touristic cities;Karanikola;Sustainability,2018

3. Environmental benefits of bike sharing: a big data-based analysis;Zhang;Appl. Energy,2018

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1. Hyper-local black carbon prediction by integrating land use variables with explainable machine learning model;Atmospheric Environment;2024-11

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